Cloud-based turbine control feedback loop

ABSTRACT

A method and apparatus for applying optimized yaw settings to wind turbines including receiving operating data from at least one wind turbine on a wind farm and sending the data to a supervisory control and data acquisition (SCADA) system on the at least one wind turbine to generate current SCADA data. The current SCADA data is sent a central processing center away from the wind farm. The central processing center includes an optimization system that can generate a new look up table (LUT) including at least one new wind turbine yaw setting calculated using information comprising wind direction, wind velocity, wind turbine location in the wind farm, information from a historic SCADA database, and yaw optimizing algorithms. The new LUT is then sent to a yaw setting selection engine (YSSE) where instructions regarding the use of the new LUT are generated.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims benefit under 35 U.S.C 119 to U.S. applicationSer. No. 62/594,980, filed on Dec. 5, 2017, and incorporated herein byreference in its entirety.

BACKGROUND

In conventional wind farms, an operating platform system may be locatedin the turbine that receives communication from a control system. Thecontrol system identifies the wind direction and signals the turbine torotate to a position 90 degrees to the direction that the wind is comingfrom or if it measures that the wind speed is too fast, it signals theturbine to shut down. There is a need to create different operationalsettings with turbines for more effective performance of the wind farms.

Additionally, when wind deflects off of wind turbines, it causes thewind to create a downstream disturbance or turbulence known as waketurbulence. Wind turbines that are downstream may perform poorly.Therefore, it is necessary to correct and steer the wake turbulence sothat wind farms have better control. There are several well-known windtheories and algorithms in the art that offer calculations to resolvethe problem of wake turbulence. However, these calculations are verycomplex, require a significant amount of computing power and areprimarily designed for research centers and not for a real timecommunications environment that would be productive in industry.Further, it may not be possible to put enough computing power at theturbine or local wind farm network to execute these calculations.Therefore, the present disclosure includes a method and system toexecute these complex calculations in a central processing center whichprovides different yaw angles to be implemented at the turbines in orderto optimize the wind farm for power production. Thus, resulting in morepowerful energy production and more profit.

BRIEF SUMMARY

A method includes receiving operating data from at least one windturbine, wherein the data includes current wind turbine operatingconditions, and the at least one wind turbine is located on a wind farm.The operating data may be sent to a supervisory control and dataacquisition (SCADA) system on the at least one wind turbine wherecurrent SCADA data may be generated. The current SCADA data is sent toan edge system located on a local network at the wind farm and then to acentral processing center in a location away from the wind farm. Thecentral processing center may include an optimization system that cangenerate a new look up table (LUT), the new LUT including at least onenew wind turbine yaw setting calculated using information comprisingwind direction, wind velocity, wind turbine location in the wind farm,information from a historic SCADA database, and yaw optimizingalgorithms. The new LUT is generated and sent to an optimizedconfiguration settings system located at the local network at the windfarm where it is next sent to a yaw setting selection engine (YSSE). TheYSSE generates instructions regarding the use of the new LUT and theinstructions are executed.

The methods of the disclosure provide steps involved in applyingoptimized yaw settings at a wind turbine in a wind farm. A method mayinclude receiving current SCADA data including a current yaw setting fora wind turbine, wherein the current SCADA data is received at a yawsetting selection engine (YSSE). Next, a determination is made if a newLUT is available using a YSSE, wherein the YSSE includes logic todetermine whether the new LUT is available, and the new LUT comprises atleast one new yaw setting. If a new LUT is available, it is received andif at least one yaw setting in the new LUT is different from a currentyaw setting, a signal is sent to an operating control system controllerto update the current yaw setting to the at least one new yaw setting onan operating control system located at the wind turbine. If the currentyaw setting is the same as the at least one new yaw setting, then themethod continues to search for an other new LUT. If a new LUT is notavailable and the prior LUT has expired, a signal is sent to theoperating control system located at the wind turbine to turn the windturbine to a default 90 degrees to the wind if wind direction or windvelocity has changed.

The disclosure provides an apparatus including a processor; and a memorystoring instructions that, when executed by the processor, to receiveoperating data from at least one wind turbine, wherein the data includescurrent wind turbine operating conditions, and the at least one windturbine is located on a wind farm. The operating data may be sent to asupervisory control and data acquisition (SCADA) system on the at leastone wind turbine where current SCADA data may be generated. The currentSCADA data is sent to an edge system located on a local network at thewind farm and then to a central processing center in a location awayfrom the wind farm. The central processing center may include anoptimization system that can generate a new look up table (LUT), the newLUT including at least one new wind turbine yaw setting calculated usinginformation comprising wind direction, wind velocity, wind turbinelocation in the wind farm, information from a historic SCADA database,and yaw optimizing algorithms. The new LUT is generated and sent to anoptimized configuration settings system located at the local network atthe wind farm where it is next sent to a yaw setting selection engine(YSSE). The YSSE generates instructions regarding the use of the new LUTand the instructions are executed.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

To easily identify the discussion of any particular element or act, themost significant digit or digits in a reference number refer to thefigure number in which that element is first introduced.

FIG. 1 illustrates a system 100 in accordance with one embodiment.

FIG. 2 illustrates a routine in accordance with one embodiment.

FIG. 3 illustrates a method 300 in accordance with one embodiment.

FIG. 4 illustrates a method 400 in accordance with one embodiment.

FIG. 5 illustrates a system 500 in accordance with one embodiment.

FIG. 6 illustrates a wind farm 600 in accordance with one embodiment.

FIG. 7 illustrates a system 700 in accordance with one embodiment.

FIG. 8 is an example block diagram of a computing device 800 that mayincorporate embodiments of the present invention.

FIG. 9 illustrates an IoT system 900 in accordance with one embodiment.

FIG. 10 illustrates SCADA data 1000 in accordance with one embodiment.

FIG. 11 illustrates SCADA data 1000 in accordance with one embodiment.

DETAILED DESCRIPTION

The present disclosure includes an input-output real-time data streamingsystem that may receive real-time sensor based and other input data froma plurality of wind farms, process the received data and securelytransmit the data in real time to a plurality of independent (andinterrelated, e.g. same owner operator) wind farms. The transmitted datamay include the computed optimal operational parameters such as digitallook up tables or local controller interpretable signals. Further, thesystem may also include a real-time feedback loop for the data to flowbetween plants and data center, for example, predicted power plantoutput versus the actual plant output. The processing of the data may beperformed in a central data-processing center outside of the local areanetwork of the wind farm such as an enterprise cloud computing systemthat may be connected to multiple different wind farms. The cloudcomputing system may generate a set of look up tables based on data fromall connected wind farms and then send the look up tables back to eachconnected wind farm.

Therefore, the present disclosure includes a method and system toexecute these complex calculations in a central processing center, whichprovides different yaw angles to be implemented at the turbines in orderto optimize the wind farm for power production. The resulting system mayproduce more powerful energy production with greater efficiency andlower operating costs.

The disclosure includes methods and systems that use an input-outputreal-time data streaming infra-structure designed to receive real-timesensor based and other input data from a plurality of wind farms. Themethods and systems may also compute high-fidelity, optimallycoordinated, intra-farm farm-wide operations. As part of communicationprocesses, the methods and systems may securely transmit operationscontrol data in real time to a plurality of independent (andinterrelated, e.g., same owner operator) wind farms.

Implementations of transmitted data may include computed optimaloperational parameters (rendered as digital look up tables or localcontroller interpretable signals). These methods and systems mayaccommodate real-time feedback loop data flows between plants and a datacenter (such as predicted power plant output versus the actual plantoutput). Flexibility in the systems may allow them to logisticallyinteract with IoT entities and\or ethernet entities, (e.g., local windfarm computer, local server, sensors, SCADA, central sensor-controllersnetworks) in order to apply machine learning and game theory moduleintelligence to further improve output. Output may be further enhancedsubject to operational or cost constraints.

Components of the system may include, but are not limited to, dataprocessing computers, arrays, and servers. Also present may behigh-capacity data storage peripherals integrated with databasemanagement components that are tailored for efficient I\O, groupsecurity architecture, and big-data anonymous historical dataaccumulation processes to address the requirements of an enterprise.

In some configurations, a cloud-based, secure, two-way communicationinfrastructure may be used. Additionally, feed-back loops and datastreaming resources of a scale able to handle big data computationalprocesses and high-speed iteration routines may be used. Examples ofcomputational demanding tasks may include 3-dimensional (or other highfidelity) aerodynamic\fluid dynamic physics models adapted for a cloudbased SaaS service and other processes integrated with big-data,high-speed iterative machine learning. Additional processes may includethose associated with game-theoretical optimizations modules.

The components may also include a central data processing center withoperational capabilities including the capability and capacity potentialto serve multiple farms, owned by respectively by multiple companies orentities, world-wide. Implicit in the latter capability and capacity isthe inclusion of ability to operate as a commercial enterprise, whichincludes, but is not limited to: technical personnel; system engineersto architect and advance the system; and modules for predicting poweroutput of multiple turbine brands as a function of the operatingparameters in this disclosure.

FIG. 1 shows a system 100 comprising a wind farm 128 that may include aturbine 104 and a LAN 106, and a central processing center 108.

The turbine 104 may include condition sensors 112, a Supervisory Controland Data Acquisition SCADA system 114, a yaw setting selection engine(YSSE) 102, an operating control system (OCS) 110 and an OCS controller126.

The local network LAN 106 may include a yaw setting selection engine(YSSE) 102, an edge system 116 and an optimized configuration settingssystem 124.

The central processing center 108 may include a historic SCADA database118, technical information 120, an optimization system 122 and anoptimized configuration settings system 124.

The condition sensors 112 may record data and send it to a SCADA systemthat resides at the turbine. The condition sensors 112 may includetemperature sensors, accelerometers, wind sensors, displacement sensorsand the like. The SCADA system identifies specific information comingfrom each turbine such as type of energy being generated, localconditions at the turbines, and the like. The SCADA system may report toan edge system 116 such as an edge computing center that may be locatedon a local network of a wind farm.

The SCADA system 114 may record wind parameters on a wind turbine suchas wind velocity and wind deviations; performance parameters, such aspower output, rotor speed, and blade pitch angle; vibration parameters,such as tower acceleration and drive train acceleration; and temperatureparameters, such as bearing temperature and gearbox temperature. Datafrom vibration and traditional measurements, together with datacollected by the turbine's SCADA systems, may be analyzed to assess anddetermine failures, detect early stage of failure, and assess thecomponent's health.

The yaw setting selection engine (YSSE) 102 may be located at the windturbine or the local network depending on the selection of wind farmoperators.

The OCS controller 126 may include an application that is software basedthat controls the operating control system (OCS) 110, and the operatingcontrol system (OCS) 110 may include a communications system.

The edge system 116 may include an edge computing center thatcommunicates SCADA data to a central processing center of the wind farmoperator.

The optimized configuration settings system 124 may be located at thelocal network of the wind farm as well as at the central processingcenter 108. It receives a generated look up table (LUT) with optimizedyaw settings and sends it to the yaw setting selection engine (YSSE)102. The optimized configuration settings system 124 may also include amemory to store the received LUT.

The central processing center may be a cloud network that processes datafor all the wind farm customers. The optimization system 122 processeshistoric data from all the wind farm, for example 5 years of SCADA datathat includes data of what happened on every wind turbine on the windfarm using technical information 120. Technical information 120 mayinclude wind theory to determine the cause of wake turbulence and windphysics systems that have been developed throughout the industry overthe years, and algorithms packaged by open source includingmodifications in order to process in a parallel environment. An exampleof the relationships between upstream and downstream wind turbines, thatmay be part of technical information 120, may be found in the articletitled Wind Plant Power Optimization Through Yaw Control Using aParametric Model for Wake Effects—A CFD Simulation Study, by Gebraad, etal., Wind Energy 2014:00, Section 3.6.

The optimization system 122 is needed because computation of theformulas requires significant computing power and is not possible atturbine 104 or LAN 106. The optimized configuration settings system 124includes a LUT with different combinations of yaw settings based on thehistoric SCADA database 118. The yaw setting selection engine (YSSE) 102performs comparisons between current Supervisory Control and DataAcquisition (SCADA) data and the LUT and makes suggestions to theoperating control system (OCS) 110 on how to apply the optimized yawsettings at the wind turbine.

For example, in one embodiment of this disclosure, the yaw settingselection engine (YSSE) 102 is located at the turbine 104 and receivesoptimized yaw settings from the central processing center via a localnetwork (LAN 106). In another embodiment, the yaw setting selectionengine (YSSE) 102 may be located at the local network (LAN 106).

In block 202 of FIG. 2, method 200 receives operating data from at leastone wind turbine, wherein the data includes current wind turbineoperating conditions, and the at least one wind turbine is located on awind farm. In block 204, method 200 sends the operating data to asupervisory control and data acquisition (SCADA) system on the at leastone wind turbine. In block 206, method 200 generates current SCADA data.In block 208, method 200 sends the current SCADA data to an edge system,wherein the edge system is located on a local network at the wind farm.In block 210, method 200 sends the current SCADA data from the edgesystem to a central processing center, wherein the central processingcenter is in a location away from the wind farm, wherein the centralprocessing center includes an optimization system that can generate anew look up table (LUT), the new LUT including at least one new windturbine yaw setting calculated using information comprising winddirection, wind velocity, wind turbine location in the wind farm,information from an historic SCADA database, and yaw optimizingalgorithms. In block 212, method 200 generates the new LUT. In block214, method 200 sends the new LUT to an optimized configuration settingssystem located at the local network at the wind farm. In block 216,method 200 sends the new LUT from the optimized configuration settingssystem to a yaw setting selection engine (YSSE), wherein the YSSEgenerates instructions regarding the use of the new LUT. In block 218,method 200 executes the instructions generated by the YSSE.

FIG. 3 includes a method 300 that shows steps involved in applying newyaw settings at a wind turbine in a wind farm. This involves receivingdata that represents wind turbine conditions at the turbine (block 302)and sending the data to a Supervisory Control and Data Acquisition(SCADA) system on the turbine (block 304). The method 300 includesgenerating current SCADA data (block 306), sending the current SCADAdata to an edge system located on a local network in the wind farm(block 308), and sending the current SCADA data from the edge system toa central processing center (block 310). The method 300 includesgenerating a new look up table by an optimization system on the centralprocessing center (block 312), sending the new look up table (LUT) to anoptimized configuration settings system (block 314), and sending the newLUT to YSSE (block 316). The method 300 includes determining whether thecurrent yaw setting is same as new yaw setting (decision block 318) and,if yes, then searching for an other LUT (block 320). If the current yawsetting is not the same as the new yaw setting, then method 300 issues acommand to operating control system located on the turbine to update thecurrent yaw setting (block 322) and applies the new yaw setting at theturbine (block 324).

An example of a look up table is as follows:

Look up table (LUT) Wind Wind Turbine #'s and Yaw Angle DirectionVelocity Frequency 1 2 3 4 0.00 4.00 2 0 0 0 6.71 0.00 5.00 5 0 0 0 3.280.00 6.00 7 0 0 0 3.45 0.00 7.00 2 0 0 0 3.42 0.00 8.00 5 0 0 0 3.51

The above table is a sample of a LUT generated by the optimizationsystem. The table includes many potential combinations of wind velocityand wind direction that have a specific yaw setting that may beimplemented for optimizing the wind farm for power production.

FIG. 4 shows a method 400 that includes steps that may be included in ayaw setting selection engine (YSEE).

The method 400 comprises determining whether a new look up table (LUT)is available (decision block 402), and if a new look up table isavailable, receiving the new look up table (block 412). The method 400compares the current Supervisory Control and Data Acquisition (SCADA)data for each turbine with yaw setting in the new LUT (block 414) anddetermines if the current yaw setting is same as the yaw setting in thenew LUT (decision block 416). If current yaw setting is same as yawsetting in the new LUT (decision block 416), then the method 400determines whether a new LUT is available (decision block 402). If thecurrent yaw setting is not same as the yaw setting in the new LUT, thenthe method 400 issues a command to the operating control system toupdate the yaw setting for each turbine requiring changes (block 418)and sends instructions to the turbines to apply new yaw setting (block420). The method 400 then determines whether a new LUT is available(decision block 402).

If a new look up table is not available, then the method 400 monitorsSCADA (block 404) and determines whether the wind direction or velocityhas changed (decision block 406). If the wind direction or velocity haschanged then method 400 determines whether the old look up table hasexpired (decision block 408). If the old LUT table has expired, then themethod 400 turns the turbine to a default 90 degrees to wind (block 410)and determines whether a new LUT is available (decision block 402). Ifthe old LUT has not expired, then the method 400 determines whether anew look up table is available (decision block 402). If the winddirection or velocity has not changed, then the method 400 continuesmonitoring SCADA (block 404).

FIG. 5 shows a system 500 that includes a central processing center 508that may be connected via cloud communications and feedback loops to thewind-plants. The central processing center 508 may include a historicSCADA database 510, technical information 502, an optimization system504 and an optimized configuration settings system 506. The SCADA datafrom edge system 514 is sent to the optimization system 504. At theoptimization system 504, a new look up table (LUT) is generated usingreceived current SCADA data, historic SCADA database 510, and algorithmsand calculations from technical information 502. This new LUT mayinclude new yaw settings. These new yaw settings are sent to anoptimized configuration settings system 506. The optimized configurationsettings system 506 sends the new LUT to a yaw setting selection engine(YSSE) (send optimized settings to YSSE 512). The YSSE may be located ona local network of the wind farm or at the turbine.

The central processing center 508 may include computers, arrays andservers. The central processing center 508 may also include group/userlevel security architectures of various components to accommodate thesecurity requirements for servicing multiple companies, I\O anddata-warehousing components for data accumulation and billing meteringand other accounting modules linked to individual customer projects,operations, or institutional usage (e.g. usage of data processing anddata-transmission resources of the enterprise, wind farm turbine numbersand configurations, and wind farm output performance).

The central data central processing center 508 may accommodate machinelearning algorithms and probabilistic models, which require substantialcomputing power. Additionally, the central processing center 508 mayprovide service for high-speed feedback loops between the remote farmlocal computer \ IoT networks, and the computer resource demanding dataprocessing center resources. In an embodiment, the central processingcenter may be connected via cloud communications and feedback loops tothe wind farms, which are customers of, or institutional subscribers to,the services of the enterprise.

FIG. 6 shows a wind farm 600 that may include wind turbine units 610,data acquisition and transmission 602, a central edge server 604, edgeanalytics 606, a yaw setting selection engine (YSSE) 612 and a centralcontrol unit 608.

The turbine units 610 may include various components such as sensors,SCADA systems, and the like. The wind farm may be located onshore,offshore, etc.

The data acquisition and transmission 602 may include a data acquisitionsystem 614 and a router 616. The data acquisition system 614, such as aSCADA system, may receive wind turbine conditions and transmit thisinformation to a central edge server 604.

The central edge server 604 may be located on a local network of a windfarm and may transmit the SCADA information to a central control unit608 such as a central processing center.

The central control unit 608 performs optimization process and returns aLUT, including yaw settings, to a yaw setting selection engine (YSSE)612. This yaw setting selection engine (YSSE) 612 may include computingdevices to compare the yaw settings with the SCADA data and generate acommand to apply the yaw settings at the turbines.

The edge analytics 606 may provide visualization of the performance ofthe wind farm with the help of computing devices.

Referring to FIG. 7, system 700 includes a turbine 710, a SCADA system718 that may be located at the turbine, a yaw setting selection engine(YSSE) 708, a local network 714, a cloud network 712 and a centralprocessing center 720.

The yaw setting selection engine (YSSE) 708 may include a memory 1 716,memory 702, a comparator 704 and a command unit 706.

The SCADA system 718 receives current turbine conditions and generatesSCADA data. This SCADA data may include a wind parameter on a windturbine, a performance parameter, a vibration parameter, a temperatureparameter, and the like.

The yaw setting selection engine (YSSE) 708 may be located at the localnetwork 714 or at the turbine 710. The yaw setting selection engine(YSSE) 708 receives the current SCADA data and a new LUT that may begenerated in a central processing center 720 on a cloud network 712. Thecurrent SCADA data including a current yaw setting may be stored inmemory 1 716 and the new LUT including a new yaw setting may be storedin memory 702. The comparator 704 compares the current SCADA data withthe new LUT. If the current yaw settings are different from the new yawsettings, then the comparator 704 may send a signal to the command unit706 that may generate a command to change the current yaw settings andapply the new yaw setting at the turbine. If the current yaw setting issame as the new yaw setting, then the command unit 706 may do nothing.If a new LUT is not available, and it has been a long period of time(e.g., 1 hour) since a new one has been provided, then the command unit706 send a command to apply a default yaw setting at the turbine 710.The default yaw setting may include turning the turbine 710 to 90degrees to the wind.

The memory units, memory 702 and memory 1 716 may include volatile ornon volatile memory.

FIG. 8 is an example block diagram of a computing device 800 that mayincorporate embodiments of the present invention. FIG. 8 is merelyillustrative of a machine system to carry out aspects of the technicalprocesses described herein and does not limit the scope of the claims.One of ordinary skill in the art would recognize other variations,modifications, and alternatives. In one embodiment, the computing device800 typically includes a monitor or graphical user interface 802, a dataprocessing system 820, a communication network interface 812, inputdevice(s) 808, output device(s) 806, and the like.

As depicted in FIG. 8, the data processing system 820 may include one ormore processor(s) 804 that communicate with a number of peripheraldevices via a bus subsystem 818. These peripheral devices may includeinput device(s) 808, output device(s) 806, communication networkinterface 812, and a storage subsystem, such as a volatile memory 810and a nonvolatile memory 814.

The volatile memory 810 and/or the nonvolatile memory 814 may storecomputer-executable instructions and thus forming logic 822 that whenapplied to and executed by the processor(s) 804 implement embodiments ofthe processes disclosed herein.

The input device(s) 808 include devices and mechanisms for inputtinginformation to the data processing system 820. These may include akeyboard, a keypad, a touch screen incorporated into the monitor orgraphical user interface 802, audio input devices such as voicerecognition systems, microphones, and other types of input devices. Invarious embodiments, the input device(s) 808 may be embodied as acomputer mouse, a trackball, a track pad, a joystick, wireless remote,drawing tablet, voice command system, eye tracking system, and the like.The input device(s) 808 typically allow a user to select objects, icons,control areas, text and the like that appear on the monitor or graphicaluser interface 802 via a command such as a click of a button or thelike.

The output device(s) 806 include devices and mechanisms for outputtinginformation from the data processing system 820. These may include themonitor or graphical user interface 802, speakers, printers, infraredLEDs, and so on as well understood in the art.

The communication network interface 812 provides an interface tocommunication networks (e.g., communication network 816) and devicesexternal to the data processing system 820. The communication networkinterface 812 may serve as an interface for receiving data from andtransmitting data to other systems. Embodiments of the communicationnetwork interface 812 may include an Ethernet interface, a modem(telephone, satellite, cable, ISDN), (asynchronous) digital subscriberline (DSL), FireWire, USB, a wireless communication interface such asBlueTooth or WiFi, a near field communication wireless interface, acellular interface, and the like.

The communication network interface 812 may be coupled to thecommunication network 816 via an antenna, a cable, or the like. In someembodiments, the communication network interface 812 may be physicallyintegrated on a circuit board of the data processing system 820, or insome cases may be implemented in software or firmware, such as “softmodems”, or the like.

The computing device 800 may include logic that enables communicationsover a network using protocols such as HTTP, TCP/IP, RTP/RTSP, IPX, UDPand the like.

The volatile memory 810 and the nonvolatile memory 814 are examples oftangible media configured to store computer readable data andinstructions to implement various embodiments of the processes describedherein. Other types of tangible media include removable memory (e.g.,pluggable USB memory devices, mobile device SIM cards), optical storagemedia such as CD-ROMS, DVDs, semiconductor memories such as flashmemories, non-transitory read-only-memories (ROMS), battery-backedvolatile memories, networked storage devices, and the like. The volatilememory 810 and the nonvolatile memory 814 may be configured to store thebasic programming and data constructs that provide the functionality ofthe disclosed processes and other embodiments thereof that fall withinthe scope of the present invention.

Logic 822 that implements embodiments of the present invention may bestored in the volatile memory 810 and/or the nonvolatile memory 814.Said logic 822 may be read from the volatile memory 810 and/ornonvolatile memory 814 and executed by the processor(s) 804. Thevolatile memory 810 and the nonvolatile memory 814 may also provide arepository for storing data used by the logic 822.

The volatile memory 810 and the nonvolatile memory 814 may include anumber of memories including a main random access memory (RAM) forstorage of instructions and data during program execution and a readonly memory (ROM) in which read-only non-transitory instructions arestored. The volatile memory 810 and the nonvolatile memory 814 mayinclude a file storage subsystem providing persistent (non-volatile)storage for program and data files. The volatile memory 810 and thenonvolatile memory 814 may include removable storage systems, such asremovable flash memory.

The bus subsystem 818 provides a mechanism for enabling the variouscomponents and subsystems of data processing system 820 communicate witheach other as intended. Although the communication network interface 812is depicted schematically as a single bus, some embodiments of the bussubsystem 818 may utilize multiple distinct busses.

It will be readily apparent to one of ordinary skill in the art that thecomputing device 800 may be a device such as a smartphone, a desktopcomputer, a laptop computer, a rack-mounted computer system, a computerserver, or a tablet computer device. As commonly known in the art, thecomputing device 800 may be implemented as a collection of multiplenetworked computing devices. Further, the computing device 800 willtypically include operating system logic (not illustrated) the types andnature of which are well known in the art.

Terms used herein should be accorded their ordinary meaning in therelevant arts, or the meaning indicated by their use in context, but ifan express definition is provided, that meaning controls.

“Circuitry” in this context refers to electrical circuitry having atleast one discrete electrical circuit, electrical circuitry having atleast one integrated circuit, electrical circuitry having at least oneapplication specific integrated circuit, circuitry forming a generalpurpose computing device configured by a computer program (e.g., ageneral purpose computer configured by a computer program which at leastpartially carries out processes or devices described herein, or amicroprocessor configured by a computer program which at least partiallycarries out processes or devices described herein), circuitry forming amemory device (e.g., forms of random access memory), or circuitryforming a communications device (e.g., a modem, communications switch,or optical-electrical equipment).

“Firmware” in this context refers to software logic embodied asprocessor-executable instructions stored in read-only memories or media.

“Hardware” in this context refers to logic embodied as analog or digitalcircuitry.

“Logic” in this context refers to machine memory circuits, nontransitory machine readable media, and/or circuitry which by way of itsmaterial and/or material-energy configuration comprises control and/orprocedural signals, and/or settings and values (such as resistance,impedance, capacitance, inductance, current/voltage ratings, etc.), thatmay be applied to influence the operation of a device. Magnetic media,electronic circuits, electrical and optical memory (both volatile andnonvolatile), and firmware are examples of logic. Logic specificallyexcludes pure signals or software per se (however does not excludemachine memories comprising software and thereby forming configurationsof matter).

“Software” in this context refers to logic implemented asprocessor-executable instructions in a machine memory (e.g. read/writevolatile or nonvolatile memory or media).

Herein, references to “one embodiment” or “an embodiment” do notnecessarily refer to the same embodiment, although they may. Unless thecontext clearly requires otherwise, throughout the description and theclaims, the words “comprise,” “comprising,” and the like are to beconstrued in an inclusive sense as opposed to an exclusive or exhaustivesense; that is to say, in the sense of “including, but not limited to.”Words using the singular or plural number also include the plural orsingular number respectively, unless expressly limited to a single oneor multiple ones. Additionally, the words “herein,” “above,” “below” andwords of similar import, when used in this application, refer to thisapplication as a whole and not to any particular portions of thisapplication. When the claims use the word “or” in reference to a list oftwo or more items, that word covers all of the following interpretationsof the word: any of the items in the list, all of the items in the listand any combination of the items in the list, unless expressly limitedto one or the other. Any terms not expressly defined herein have theirconventional meaning as commonly understood by those having skill in therelevant art(s).

Various logic functional operations described herein may be implementedin logic that is referred to using a noun or noun phrase reflecting saidoperation or function. For example, an association operation may becarried out by an “associator” or “correlator.” Likewise, switching maybe carried out by a “switch”, selection by a “selector,” and so on.

FIG. 9 illustrates an IoT system 900 in one embodiment. The methods andsystems of the disclosure may interact with IoT entities and\or ethernetentities, (e.g., local wind farm computer, local server, sensors, SCADA,central sensor-controllers networks). The IoT system 900 comprises IoTdevices 902 communicatively coupled via a wide area network 904 to aserver system 906 via an optional proxy server 910. The network topologyof the IoT system 900 is a hybrid hub-and-spoke. One or more of the IoTdevices 902 acts as a gateway device 908 providing a communicationchannel to the server system 906. The IoT devices 902 that are not thegateway device 908 communicate directly with the gateway device 908, orvia the proxy server 910, which communicates on their behalf and on itsown behalf with the server system 906. The optional proxy server 910 mayimprove the performance of the IoT system 900 by mirroring some or allof the state of the server system 906 and thus enabling the IoT devices902 to communicate without creating bandwidth or incurring the latencyof the wide area network 904. The optional proxy server 910 is typicallycolocated at a facility or nearby facility to where the IoT devices 902are located.

Referring to FIG. 10, an example a code for SCADA data 1000 is shown.The SCADA data 1000 may include several parameters such as a windparameter on a wind turbine, a performance parameter, a vibrationparameter, a temperature parameter, and the like.

FIG. 11 is a continuation of the code for SCADA data 1000. The SCADAdata 1000 may further include parameters such as yaw angle, blade pitchangle, etc.

The methods and systems in this disclosure are described in thepreceding on the basis of several preferred embodiments. Differentaspects of different variants are considered to be described incombination with each other such that all combinations that upon readingby a skilled person in the field on the basis of this document may beregarded as being read within the concept of the invention. Thepreferred embodiments do not limit the extent of protection of thisdocument.

Having thus described embodiments of the present invention of thepresent application in detail and by reference to illustrativeembodiments thereof, it will be apparent that modifications andvariations are possible without departing from the scope of the presentinvention.

1. A method comprising, receiving operating data from at least one windturbine, wherein the data includes current wind turbine operatingconditions, and the at least one wind turbine is located on a wind farm;sending the operating data to a supervisory control and data acquisition(SCADA) system on the at least one wind turbine; generating currentSCADA data; sending the current SCADA data to an edge system, whereinthe edge system is located on a local network at the wind farm; sendingthe current SCADA data from the edge system to a central processingcenter, wherein the central processing center is in a location away fromthe wind farm, wherein the central processing center includes anoptimization system that can generate a new look up table (LUT), the newLUT including at least one new wind turbine yaw setting calculated usinginformation comprising wind direction, wind velocity, wind turbinelocation in the wind farm, information from a historic SCADA database,and yaw optimizing algorithms; generating the new LUT; sending the newLUT to an optimized configuration settings system located at the localnetwork at the wind farm; sending the new LUT from the optimizedconfiguration settings system to a yaw setting selection engine (YSSE),wherein the YSSE generates instructions regarding the use of the newLUT; and executing the instructions generated by the YSSE to set a yawof the at least one wind turbine.
 2. The method of claim 1, wherein thelocation of the YSSE is at least one of the wind turbine, the localnetwork at the wind farm, and combinations thereof.
 3. The method ofclaim 1, wherein the YSEE comprises logic to: determine whether a newLUT is available; on condition the new LUT is available, generateinstructions to: receive the new LUT; compare the current yaw settingwith an at least one new yaw setting: on condition that the current yawsetting is not same as the at least one new yaw setting: send a signalto an operating control system controller to update the current yawsetting to the at least one new yaw setting on an operating controlsystem located at the wind turbine; apply the at least one new yawsetting to the operating control system; and on condition that thecurrent yaw setting is same as the at least one new yaw setting: searchfor an other new LUT; on condition the new LUT is not available,generate instructions to: monitor SCADA data using the YSSE; send acommand to the operating control system located at the wind turbine toturn the wind turbine to a default 90 degrees to the wind if winddirection or wind velocity has changed and a prior LUT is expired,wherein the prior LUT is a LUT that was available before the new LUT;and apply the command to the operating control system of the windturbine.
 4. The method of claim 1, further comprising: receiving apredicted wind farm power output from the central processing center;measuring an actual wind farm power output after the at least one newyaw setting has been applied; and comparing the predicted wind farmpower output to the actual wind farm power output.
 5. The method ofclaim 4, further comprising: providing feedback to the centralprocessing center regarding the comparison between the predicted windfarm power output the actual wind farm power output and generatinginstructions to: on condition that the predicted wind farm power outputis higher than the actual wind farm power output: generate a new LUTbased on the feedback, wherein the new LUT includes yaw settings thatare predicted to increase the actual wind farm power output; send thenew LUT to the optimized configuration settings system; and on conditionthat the actual wind farm power output is higher than the predicted windfarm power output: update at least one of the information in thehistoric SCADA database, the yaw optimizing algorithms, and combinationsthereof to enable a future predicted wind farm power output to be closerto the actual wind farm power output; and executing the instructions. 6.The method of claim 4, wherein the predicted wind farm power output isbased on predicted optimal yaw settings.
 7. The method of claim 1,wherein the location of the optimized configuration settings system isat least one of the central processing center, the local network at thewind farm, and combinations thereof. 8-18. (canceled)
 19. A computingapparatus, the computing apparatus comprising: a processor; and a memorystoring instructions that, when executed by the processor, configure theapparatus to, receive operating data from at least one wind turbine,wherein the data includes current wind turbine operating conditions, andthe at least one wind turbine is located on a wind farm; send theoperating data to a supervisory control and data acquisition (SCADA)system on the at least one wind turbine; generate current SCADA data;send the current SCADA data to an edge system, wherein the edge systemis located on a local network at the wind farm; send the current SCADAdata from the edge system to a central processing center, wherein thecentral processing center is in a location away from the wind farm,wherein the central processing center includes an optimization systemthat can generate a new look up table (LUT), the new LUT including atleast one new wind turbine yaw setting calculated using informationcomprising wind direction, wind velocity, wind turbine location in thewind farm, information from a historic SCADA database, and yawoptimizing algorithms; generate the new LUT; send the new LUT to anoptimized configuration settings system located at the local network atthe wind farm; send the new LUT from the optimized configurationsettings system to a yaw setting selection engine (YSSE), wherein theYSSE generates instructions regarding the use of the new LUT; andexecute the instructions generated by the YSSE to set a yaw of the atleast one wind turbine.
 20. The computing apparatus of claim 19, whereinthe YSEE comprises logic to: determine whether a new LUT is available;on condition the new LUT is available, generate instructions to: receivethe new LUT; compare the current yaw setting with an at least one newyaw setting: on condition that the current yaw setting is not same asthe at least one new yaw setting: send a signal to an operating controlsystem controller to update the current yaw setting to the at least onenew yaw setting on an operating control system located at the windturbine; apply the at least one new yaw setting to the operating controlsystem; and on condition that the current yaw setting is same as the atleast one new yaw setting: search for an other new LUT; on condition thenew LUT is not available, generate instructions to: monitor SCADA datausing the YSSE; send a command to the operating control system locatedat the wind turbine to turn the wind turbine to a default 90 degrees tothe wind if wind direction or wind velocity has changed and a prior LUTis expired, wherein the prior LUT is a LUT that was available before thenew LUT; and apply the command to the operating control system of thewind turbine.